Report

Introduction

• This dataset encapsulates a comprehensive collection of financial information, spanning multiple stocks within the Nifty 50 index. It comprises a rich array of data points, including stock prices, trading volumes, and related metrics, amassed over a substantial timeframe. This dataset serves as a valuable resource for analyzing market trends, assessing stock performances, and deriving insights crucial for informed investment strategies and comprehensive market evaluations.

• The Nifty 50 index represents a collection of 50 actively traded Indian stocks listed on the National Stock Exchange (NSE). These stocks are chosen based on various factors like market capitalization, liquidity, and other financial parameters. The index serves as a benchmark for the Indian stock market, reflecting the performance of these select companies across diverse sectors, offering a snapshot of the overall market movements.

• Regarding the dataset, it encompasses a wide array of financial metrics for stocks within the Nifty 50 index. This includes historical stock prices, trading volumes, market indicators, fundamental ratios, and potentially other relevant data points.

• Constraints within this dataset might include factors such as:

1. Timeframe: Data might be available within a specific time range due to historical limitations or data collection constraints.
2. Availability of Metrics: Some metrics or specific data points might be missing or incomplete due to various reasons, like unreported values or data collection issues.
3. Accuracy: The dataset's accuracy might be influenced by factors like reporting errors or discrepancies in the data sources.
4. Granularity: Depending on the source, the dataset might have limitations in granularity, such as daily, weekly, or monthly data, which could impact detailed analysis at a more refined time scale.

• The dataset's richness and comprehensive nature make it a valuable tool for conducting in-depth analysis, identifying market trends, evaluating stock performances, and formulating informed investment strategies within the context of the Indian stock market

import pandas as pd
import glob
import matplotlib.pyplot as plt
import seaborn as sns

Reading all the CSV files

file_list = glob.glob('C:/Users/devan/Desktop/Big Data Analytics/Final Project/*.csv')
data_frames = []
for file in file_list:
    data = pd.read_csv(file)
    data_frames.append(data)
nifty_data = pd.concat(data_frames, ignore_index=True)

This code compiles data from multiple CSV files located in a specified directory. It first collects a list of file paths using 'glob.glob', then reads each CSV file using Pandas' 'read_csv' function and stores the data in a list of data frames. Finally, it merges these separate data frames into a single comprehensive DataFrame named 'nifty_data' using 'pd.concat', providing a consolidated dataset that aggregates information from all the CSV files for streamlined analysis within the context of Big Data Analytics.

nifty_data.head()

	Date	Symbol	Series	Prev Close	Open	High	Low	Last	Close	VWAP	Volume	Turnover	Trades	Deliverable Volume	%Deliverble	Company Name	Industry	ISIN Code
0	2007-11-27	MUNDRAPORT	EQ	440.00	770.00	1050.00	770.0	959.0	962.90	984.72	27294366.0	2.687719e+15	NaN	9859619.0	0.3612	NaN	NaN	NaN
1	2007-11-28	MUNDRAPORT	EQ	962.90	984.00	990.00	874.0	885.0	893.90	941.38	4581338.0	4.312765e+14	NaN	1453278.0	0.3172	NaN	NaN	NaN
2	2007-11-29	MUNDRAPORT	EQ	893.90	909.00	914.75	841.0	887.0	884.20	888.09	5124121.0	4.550658e+14	NaN	1069678.0	0.2088	NaN	NaN	NaN
3	2007-11-30	MUNDRAPORT	EQ	884.20	890.00	958.00	890.0	929.0	921.55	929.17	4609762.0	4.283257e+14	NaN	1260913.0	0.2735	NaN	NaN	NaN
4	2007-12-03	MUNDRAPORT	EQ	921.55	939.75	995.00	922.0	980.0	969.30	965.65	2977470.0	2.875200e+14	NaN	816123.0	0.2741	NaN	NaN	NaN

What are the data types?

nifty_data = nifty_data.astype({'Symbol': 'category'})
nifty_data.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 470434 entries, 0 to 470433
Data columns (total 18 columns):
 #   Column              Non-Null Count   Dtype   
---  ------              --------------   -----   
 0   Date                470384 non-null  object  
 1   Symbol              470434 non-null  category
 2   Series              470434 non-null  object  
 3   Prev Close          470384 non-null  float64 
 4   Open                470384 non-null  float64 
 5   High                470384 non-null  float64 
 6   Low                 470384 non-null  float64 
 7   Last                470384 non-null  float64 
 8   Close               470384 non-null  float64 
 9   VWAP                470384 non-null  float64 
 10  Volume              470384 non-null  float64 
 11  Turnover            470384 non-null  float64 
 12  Trades              240688 non-null  float64 
 13  Deliverable Volume  438230 non-null  float64 
 14  %Deliverble         438230 non-null  float64 
 15  Company Name        50 non-null      object  
 16  Industry            50 non-null      object  
 17  ISIN Code           50 non-null      object  
dtypes: category(1), float64(12), object(5)
memory usage: 61.5+ MB

nifty_data.Symbol.unique()

['MUNDRAPORT', 'ADANIPORTS', 'ASIANPAINT', 'UTIBANK', 'AXISBANK', ..., 'VEDL', 'WIPRO', 'ZEETELE', 'ZEEL', 'INFRATEL']
Length: 66
Categories (66, object): ['ADANIPORTS', 'ASIANPAINT', 'AXISBANK', 'BAJAJ-AUTO', ..., 'VEDL', 'WIPRO', 'ZEEL', 'ZEETELE']

Finding unique values (stocks) from the dataset.

Descriptive statistics of the dataset.

nifty_data.shape

(470434, 18)

nifty_data.describe()

	Prev Close	Open	High	Low	Last	Close	VWAP	Volume	Turnover	Trades	Deliverable Volume	%Deliverble
count	470384.000000	470384.000000	470384.000000	470384.000000	470384.000000	470384.000000	470384.000000	4.703840e+05	4.703840e+05	2.406880e+05	4.382300e+05	438230.000000
mean	1266.196349	1267.759708	1286.581440	1247.488465	1266.388302	1266.554351	1267.132300	3.045903e+06	1.610138e+14	6.196427e+04	1.315098e+06	0.502997
std	2581.367576	2585.256861	2619.646432	2546.618689	2581.389799	2582.138197	2582.697234	7.333973e+06	3.298082e+14	6.866443e+04	2.831667e+06	0.190019
min	0.000000	8.500000	9.750000	8.500000	9.100000	9.150000	9.210000	3.000000e+00	1.047000e+07	1.100000e+01	5.000000e+00	0.023600
25%	274.300000	275.000000	279.500000	269.600000	274.400000	274.350000	274.697500	2.190095e+05	1.612816e+13	2.183400e+04	1.253825e+05	0.364700
50%	566.500000	567.025000	576.900000	556.500000	567.000000	566.700000	566.940000	1.010938e+06	6.832603e+13	4.406800e+04	5.017560e+05	0.511000
75%	1242.200000	1243.312500	1263.000000	1221.650000	1242.900000	1242.400000	1242.662500	3.019851e+06	1.863835e+14	7.893550e+04	1.452238e+06	0.638400
max	32861.950000	33399.950000	33480.000000	32468.100000	32849.000000	32861.950000	32975.240000	4.810589e+08	3.564334e+16	1.643015e+06	2.325307e+08	1.000000

• The descriptive statistics presented here offer insights into various aspects of a financial dataset related to stock market trading. These statistics provide a summary overview of the numerical attributes within the dataset, shedding light on the stock market's price movements and trading volumes.

• The 'count' row indicates the total number of observations for each column, implying the quantity of available data points for analysis. The 'mean' row showcases the average values for each attribute, providing a central tendency measure for the dataset. Meanwhile, the 'std' row illustrates the standard deviation, signifying the extent of variability or dispersion around the mean.

• The 'min' and 'max' rows signify the minimum and maximum values observed in each column, outlining the range of values present in the dataset. The '25%', '50%', and '75%' rows correspond to the first quartile (25th percentile), median (50th percentile), and third quartile (75th percentile), respectively. These percentiles offer insights into the distribution and spread of the data, indicating the values below which a certain percentage of observations lie.

• These descriptive statistics aid in understanding the range, central tendency, and dispersion of stock prices, trading volumes, and related metrics. They facilitate preliminary assessments of data characteristics, aiding analysts and investors in making informed decisions and formulating strategies based on historical market behavior.

Finding null values in the dataset

nifty_data.isna().sum()

Date                      50
Symbol                     0
Series                     0
Prev Close                50
Open                      50
High                      50
Low                       50
Last                      50
Close                     50
VWAP                      50
Volume                    50
Turnover                  50
Trades                229746
Deliverable Volume     32204
%Deliverble            32204
Company Name          470384
Industry              470384
ISIN Code             470384
dtype: int64

nifty_data['Date'] = pd.to_datetime(nifty_data['Date'])

nifty_data['Year'] = nifty_data['Date'].dt.year
nifty_data_yearly = nifty_data.groupby('Year')[['High', 'Low']].mean()
plt.figure(figsize=(10, 6))
bar_width = 0.35
index = nifty_data_yearly.index
plt.bar(index - bar_width/2, nifty_data_yearly['High'], bar_width, color='blue', label='High')
plt.bar(index + bar_width/2, nifty_data_yearly['Low'], bar_width, color='red', label='Low')
plt.title('Nifty 50 Index Changes (2000 - 2021)')
plt.xlabel('Year')
plt.ylabel('Average Nifty 50 Index Value')
plt.legend()
plt.xticks(index)
plt.grid(axis='y')
plt.tight_layout()
plt.show()

• A visual representation showcasing the annual high-low ranges of the Nifty Fifty through a bar graph provides a comprehensive overview of the market's yearly price volatility.

for stock in nifty_data['Symbol'].unique():
    plt.figure(figsize=(8, 5))  # Each stock gets its own plot
    temp_df = nifty_data[nifty_data['Symbol'] == stock]
    
    # Group data by year and calculate the mean 'Close' and 'Open' values for each year
    yearly_data = temp_df.groupby(temp_df['Date'].dt.year)[['High', 'Low']].mean()
    
    plt.plot(yearly_data.index, yearly_data['High'], marker='o', label='High')
    plt.plot(yearly_data.index, yearly_data['Low'], marker='o', label='Low')
    
    plt.title(f"Nifty 50 Index for '{stock}' (Close and Open) by Year")
    plt.xlabel('Year')
    plt.ylabel('price')
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()

• This code segment utilizes Python and Matplotlib to generate individual line plots representing the annual mean high and low prices of stocks within the Nifty 50 index. For each unique stock symbol in the dataset, the code creates a distinct plot, adjusting the figure size accordingly.

• By isolating the data for each stock symbol, the code groups the information by year, calculating the average high and low prices for every year using the 'groupby' function. The resulting line plots display trends in these yearly average high and low prices, showcasing the fluctuation patterns over time for each stock within the Nifty 50 index.

• This visualization strategy facilitates a clear comparison of how high and low prices have trended annually for different stocks. Investors and analysts can interpret these trends to identify historical patterns, assess market volatility, and gain insights into potential price ranges for various stocks over the years, aiding in informed decision-making and strategic analysis within the realm of stock market investments.

nifty_blank = ['JSWSTL','INFRATEL']
nifty_data[nifty_data['Symbol'].isin(nifty_blank)]

	Date	Symbol	Series	Prev Close	Open	High	Low	Last	Close	VWAP	Volume	Turnover	Trades	Deliverable Volume	%Deliverble	Company Name	Industry	ISIN Code	Year
127798	2005-03-23	JSWSTL	EQ	10.00	455.00	458.50	383.60	386.9	390.15	419.86	2087710.0	8.765375e+13	NaN	382057.0	0.1830	NaN	NaN	NaN	2005.0
127799	2005-03-24	JSWSTL	EQ	390.15	392.85	398.50	357.50	371.8	369.20	372.01	1226479.0	4.562638e+13	NaN	232172.0	0.1893	NaN	NaN	NaN	2005.0
127800	2005-03-28	JSWSTL	EQ	369.20	376.70	394.05	375.00	380.0	378.85	383.64	1235794.0	4.741048e+13	NaN	263415.0	0.2132	NaN	NaN	NaN	2005.0
127801	2005-03-29	JSWSTL	EQ	378.85	382.90	383.80	363.25	369.1	368.05	375.26	624072.0	2.341915e+13	NaN	198916.0	0.3187	NaN	NaN	NaN	2005.0
127802	2005-03-30	JSWSTL	EQ	368.05	367.00	371.90	360.05	362.7	362.15	365.13	466349.0	1.702775e+13	NaN	159641.0	0.3423	NaN	NaN	NaN	2005.0
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
281417	2005-09-12	JSWSTL	EQ	282.60	285.00	291.00	285.00	289.0	288.25	288.71	421914.0	1.218089e+13	NaN	271520.0	0.6435	NaN	NaN	NaN	2005.0
281418	2005-09-13	JSWSTL	EQ	288.25	288.50	303.00	287.10	296.6	297.50	295.89	667860.0	1.976153e+13	NaN	399014.0	0.5975	NaN	NaN	NaN	2005.0
281419	2005-09-14	JSWSTL	EQ	297.50	299.00	307.50	291.10	294.3	295.40	301.00	648158.0	1.950985e+13	NaN	291204.0	0.4493	NaN	NaN	NaN	2005.0
281420	2005-09-15	JSWSTL	EQ	295.40	297.00	299.00	294.95	296.0	296.50	297.00	371305.0	1.102761e+13	NaN	216658.0	0.5835	NaN	NaN	NaN	2005.0
417065	NaT	INFRATEL	EQ	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	Bharti Infratel Ltd.	TELECOM	INE121J01017	NaN

247 rows × 19 columns

symbols_to_drop = ['JSWSTL', 'INFRATEL']
nifty_data_2 = nifty_data[~nifty_data['Symbol'].isin(symbols_to_drop)]

• Excluding the symbols 'JSWSTL' and 'INFRATEL' from the dataset due to inadequate available data, aiming to ensure data integrity and analytical robustness throughout the analysis process.

A correlation matrix was generated to analyze the relationships between chosen stocks, outlined and elaborated upon in the report. This matrix provides insights into how the price movements of these stocks relate to each other, aiding in understanding potential patterns or dependencies in their behavior.

corr = nifty_data_2[nifty_data_2['Symbol']== 'HEROMOTOCO'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\4069535145.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HEROMOTOCO'].corr()

<Axes: >

corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFC'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\728104081.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFC'].corr()

<Axes: >

corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFCBANK'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\83096412.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HDFCBANK'].corr()

<Axes: >

corr = nifty_data_2[nifty_data_2['Symbol']== 'HCLTECH'].corr() 
plt.figure(figsize=(10,10))
sns.heatmap(corr, annot=True, cmap="coolwarm")

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\251171166.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.
  corr = nifty_data_2[nifty_data_2['Symbol']== 'HCLTECH'].corr()

<Axes: >

• A correlation matrix for stocks such as 'HEROMOTOCO','HDFC', 'HDFC BANK', and 'HCL TECH' enables an extensive analysis of how its price movements align or diverge with other variables. This matrix quantifies the degree and direction of linear relationships between 'HEROMOTOCO' and the mentioned stocks, assigning values from -1 to 1. These values signify the strength and nature of correlations: 1 denotes a perfect positive correlation, -1 represents a perfect negative correlation, and 0 suggests no linear relationship. Such an analysis aids investors and analysts in understanding potential associations or diversifications within a portfolio, facilitating informed decisions based on historical price behaviors and their interconnections.

Assessing the performance of individual stocks from 2000 to 2021 by investing 32,000 INR equally in 2000 and determining the value in 2021. This analysis aims to gauge the growth or decline of the initial investment, providing insights into the long-term returns generated by each stock.

invested_amount_2000 = 500

unique_symbols = nifty_data_2['Symbol'].unique()
results_df = pd.DataFrame(columns=['Symbol', 'First_Open_2000','Invested_amount_2000', 'Last_Close_2021', 'Return_Amount_2021','Net_Worth'])
for symbol in unique_symbols:
    symbol_data = nifty_data_2[nifty_data_2['Symbol'] == symbol]
    symbol_data = symbol_data.sort_values(by='Year')
    first_open_value = symbol_data['Open'].first_valid_index()
    first_open = symbol_data.loc[first_open_value, 'Open'] if first_open_value is not None else None
    last_close_value = symbol_data['Close'].last_valid_index()
    last_close = symbol_data.loc[last_close_value, 'Close'] if last_close_value is not None else None
    return_amount_2021 = invested_amount_2000 * last_close / first_open if (first_open is not None and last_close is not None) else None
    net = return_amount_2021 - invested_amount_2000
    results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)

results_df

	Symbol	First_Open_2000	Invested_amount_2000	Last_Close_2021	Return_Amount_2021	Net_Worth
0	MUNDRAPORT	770.0	500	135.50	87.987013	-412.012987
1	ADANIPORTS	137.1	500	730.05	2662.472648	2162.472648
2	ASIANPAINT	370.0	500	2536.40	3427.567568	2927.567568
3	UTIBANK	26.7	500	597.50	11189.138577	10689.138577
4	AXISBANK	588.0	500	714.90	607.908163	107.908163
...	...	...	...	...	...	...
59	SSLT	185.0	500	220.15	595.000000	95.000000
60	VEDL	218.4	500	257.25	588.942308	88.942308
61	WIPRO	2724.0	500	492.75	90.446035	-409.553965
62	ZEETELE	1175.0	500	238.35	101.425532	-398.574468
63	ZEEL	230.0	500	185.60	403.478261	-96.521739

64 rows × 6 columns

unique_symbols = results_df['Symbol'].unique()
for symbol in unique_symbols:
    symbol_data = results_df[results_df['Symbol'] == symbol]
    plt.figure(figsize=(6, 4))
    plt.bar(['Invested 2000', 'Return 2021'], [symbol_data['Invested_amount_2000'].iloc[0], symbol_data['Return_Amount_2021'].iloc[0]])
    plt.xlabel('Amount')
    plt.ylabel('Value')
    plt.title(f'Invested Amount in 2000 vs Return Amount in 2021 - {symbol}')
    plt.tight_layout()
    plt.show()

results_df['Price_Difference'] = results_df['Last_Close_2021'] - results_df['First_Open_2000']
max_row = results_df.loc[results_df['Price_Difference'].idxmax()]
print("Stock with maximum growth as on 2021:")
print(max_row)

Stock with maximum growth as on 2021:
Symbol                       SHREECEM
First_Open_2000                  68.0
Invested_amount_2000              500
Last_Close_2021               27910.5
Return_Amount_2021      205224.264706
Net_Worth               204724.264706
Price_Difference              27842.5
Name: 46, dtype: object

• Determining the stock with the highest return.

Calculating the present value of a portfolio evenly distributed across multiple stocks since 2000, starting with an initial investment of 64,000 INR, and assessing its current worth in 2021 to evaluate the overall performance of the investment.

invested_amount_2000 = 1000

unique_symbols = nifty_data_2['Symbol'].unique()
results_df = pd.DataFrame(columns=['Symbol', 'First_Open_2000','Invested_amount_2000', 'Last_Close_2021', 'Return_Amount_2021','Net_Worth'])
for symbol in unique_symbols:
    symbol_data = nifty_data_2[nifty_data_2['Symbol'] == symbol]
    symbol_data = symbol_data.sort_values(by='Year')
    first_open_value = symbol_data['Open'].first_valid_index()
    first_open = symbol_data.loc[first_open_value, 'Open'] if first_open_value is not None else None
    last_close_value = symbol_data['Close'].last_valid_index()
    last_close = symbol_data.loc[last_close_value, 'Close'] if last_close_value is not None else None
    return_amount_2021 = invested_amount_2000 * last_close / first_open if (first_open is not None and last_close is not None) else None
    net = return_amount_2021 - invested_amount_2000
    results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)

C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)
C:\Users\devan\AppData\Local\Temp\ipykernel_16832\2321537900.py:12: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.
  results_df = results_df.append({'Symbol': symbol, 'First_Open_2000': first_open,'Invested_amount_2000':invested_amount_2000 ,'Last_Close_2021': last_close, 'Return_Amount_2021': return_amount_2021,'Net_Worth':net}, ignore_index=True)

results_df

	Symbol	First_Open_2000	Invested_amount_2000	Last_Close_2021	Return_Amount_2021	Net_Worth
0	MUNDRAPORT	770.0	1000	135.50	175.974026	-824.025974
1	ADANIPORTS	137.1	1000	730.05	5324.945295	4324.945295
2	ASIANPAINT	370.0	1000	2536.40	6855.135135	5855.135135
3	UTIBANK	26.7	1000	597.50	22378.277154	21378.277154
4	AXISBANK	588.0	1000	714.90	1215.816327	215.816327
...	...	...	...	...	...	...
59	SSLT	185.0	1000	220.15	1190.000000	190.000000
60	VEDL	218.4	1000	257.25	1177.884615	177.884615
61	WIPRO	2724.0	1000	492.75	180.892070	-819.107930
62	ZEETELE	1175.0	1000	238.35	202.851064	-797.148936
63	ZEEL	230.0	1000	185.60	806.956522	-193.043478

64 rows × 6 columns

plt.figure(figsize=(6, 4))
plt.bar(['Invested 2000', 'Return 2021'], [results_df['Invested_amount_2000'].sum(), results_df['Return_Amount_2021'].sum()])
plt.xlabel('Amount')
plt.ylabel('Value')
plt.title('Invested Amount in 2000 vs Return Amount in 2021')
plt.tight_layout()
plt.show()

results_df['Net_Worth'].sum()-results_df['Invested_amount_2000'].sum()

648661.901070853

percentage_value = round((results_df['Net_Worth'].sum() - results_df['Invested_amount_2000'].sum()) * 100 / results_df['Invested_amount_2000'].sum(), 2)
result_with_percentage = str(percentage_value) + '%'
result_with_percentage

'1013.53%'

• Profit percentage as on year 2021.

Conclusion

• The portfolio exhibited an exceptional growth of 1013.53% from its 2000 inception, translating an initial investment of 64000 INR into a substantial profit of 648661.90 INR by the end of 2021.
• In summary, diving into this dataset has been eye-opening. We've seen how stock prices and trading volumes vary across different companies in the Nifty 50 index, showing us how the market moves. Looking at correlations between stocks helped us understand how they relate, guiding us on how to spread investments for safety. Plus, simulating past investments gave us a glimpse into potential portfolio growth or decline. Altogether, this data is a goldmine for making smarter investment decisions.